Abstract:

A counter-terrorism underwater surveillance system for detecting swimming
intruders includes a sonar array 20 comprising a plurality of sensor
elements which both transmit and receive acoustic signals. Power
amplifiers 22 generate electric transmit signals which are converted to
acoustic form for transmission by the sonar array 20. Incoming acoustic
signals, including echo data from any intruder in the water, are received
by the sonar array 20 and passed to a data acquisition subsystem 24,
which digitises the data for processing. The digitised data is passed to
a beamforming subsystem 26 which forms defined beams from omni-element
data. A detection processing subsystem 28 then extracts signals from
noise and reverberation and passes these to a display processing
subsystem 30 which defines tracks from the intruder echo data. Finally,
intruder images and tracks are displayed on a display subsystem 32. The
beamforming subsystem processes outputs of the sonar array subsystem by
means of a pseudo-circular convolution technique thereby to form defined
beams.

Claims:

1. An underwater surveillance system including:a sensor array subsystem
configured and arranged for immersion in a body of water to transmit and
receive sonar signals and comprising a plurality of piezoelectric
elements arcuately spaced apart azimuthally around an angle θ;a
data acquisition subsystem operatively connected to the sensor array
subsystem to digitise data therefrom; anda beamforming subsystem
operatively connected to the data acquisition subsystem;wherein the
beamforming subsystem is operative to process outputs of the sonar array
subsystem by means of a pseudo-circular convolution technique thereby to
form defined beams.

2-22. (canceled)

23. A beamformer for forming defined beams by processing signals from a
sensor array, wherein said beamformer includes pseudo-circular
convolution means for processing said signals.

24. A beamformer as claimed in claim 23 wherein said beamformer includes
replica correlation processing operative by fast convolution of complex
blocks of data from each element of the sonar array subsystem to form
multiple receive beams.

25. In a beamformer as claimed in claim 24, a method of processing the
blocks of data comprising the steps of:(a) transforming the time-domain
data block into a plurality of cells in the frequency domain by means of
a 64 k point fast Fourier transform (FFT),(b) fast replica correlation by
means of 64 k point vector multiplication of each of the frequency domain
data block outputs,(c) fast pseudo-circular convolution implemented
across the elements for each frequency cell, thereby to generate
frequency domain beam data, and(d) 64 k point inverse FFT (IFFT) to
return to the time domain.

26. An underwater surveillance system including:a sensor array subsystem
configured and arranged for immersion in a body of water to transmit and
receive sonar signals and comprising a plurality of piezoelectric
elements arcuately spaced apart azimuthally around an angle θ;a
data acquisition subsystem operatively connected to the sensor array
subsystem to digitise data therefrom; anda beamforming subsystem
operatively connected to the data acquisition subsystem;wherein the
beamforming subsystem comprises a beamformer as claimed in claim 23
operative to process outputs of the sonar array subsystem and thereby
form defined beams.

27. An underwater surveillance system as claimed in claim 26 wherein:the
array comprises P hydrophones and the beamformer is configured and
arranged to form P contiguous beams from an arc of the array comprising Q
said hydrophones;Q is less than P; andP+Q is less than or equal to an
integer power of 2.

28. An underwater surveillance system as claimed in claim 27 wherein P=360
and Q≦152.

30. An underwater surveillance system as claimed in claim 29 wherein the
wave digital filters provide out of band rejection of greater then 120
dB, with in band ripple less than 0.1 dB and with a pass band to stop
band transition bandwidth less than 4 kHz.

31. An underwater surveillance system as claimed in claim 30 wherein the
data acquisition subsection dissipates less than 150 mW per channel
whilst maintaining 20-bit precision.

32. An underwater surveillance system as claimed in claim 26 wherein the
sensor array is divided into a plurality of sectors configured and
arranged to provide a specified azimuthal spread, each said sector having
an angular dimension of 45.degree. in azimuth.

33. An underwater surveillance system as claimed in claim 26 wherein the
sensor array comprises a 1-3 piezo-composite material impedance matched
to the water.

34. An underwater surveillance system as claimed in claim 33 wherein the
piezo-composite material is curved by a kerfing process entailing
preferentially cutting wider kerfs between active transducer areas.

35. An underwater surveillance system as claimed in claim 26 wherein the
multiple receive beams are azimuthally narrow, whereby the system
provides high angular resolution.

36. An underwater surveillance system as claimed in claim 35 wherein the
azimuthal beamwidth of each beam is 1.degree..

37. An underwater surveillance system as claimed in claim 36 wherein the
elevational beamwidth of each beam is 10.degree..

38. An underwater surveillance system as claimed in claim 26 wherein the
system operates at about 100 kHz and the sonar array has dimensions of
about 850 mm horizontally and 85 mm vertically.

40. An underwater surveillance system as claimed in claim 26 wherein the
system includes a power amplification subsystem operatively connected to
the sensor array subsystem and configured and arranged to deliver thereto
at least 215 dB relative to μPa at 1 m.

41. An underwater surveillance system as claimed in claim 26 wherein the
system includes:a detection processing system operatively connected to
the beamforming subsystem and configured and arranged to extract intruder
echo data from noise and reverberation;a display processing subsystem
operatively connected to the detection processing subsystem and operative
to define tracks from the intruder echo data; anda display subsystem
operatively connected to the display processing subsystem to display
intruder images and tracks.

Description:

[0002]Worldwide, there are innumerable locations which demand underwater
surveillance to detect swimming intruders who may be equipped with
self-contained underwater breathing apparatus (SCUBA) or the like. In
such locations intruder detection may be required to meet a wide variety
of needs including: protecting bridges, dams, power plants, industrial
installations and other waterfront facilities; monitoring port usage
and/or traffic patterns; protecting docksides and channels; safeguarding
shore based facilities; protecting individual vessels; portable
expeditionary uses; use in permanent or otherwise fixed applications;
protecting waterfront facilities; recovery of or from shipwreck, lost
artefacts and other disasters; temporary border demarcation in wartime or
otherwise; and counterintelligence operations. Possible intruders to
which such locations may be vulnerable include, as well as thieves, enemy
combatants, insurgents and terrorists.

[0003]Underwater intruder detection systems must provide sufficient
resolution to distinguish an intruder who may be a single swimmer,
approaching from any direction and at a distance (say 1000 m) allowing
countermeasures to be implemented. In principle the design of such
systems could be based upon techniques used in known minehunting systems,
say, but heretofore these have employed large aperture sonar arrays and
wide processing bandwidths--several hundred staves of hydrophones,
wide-band coded transmissions and pulse compression processing
techniques. The use of 1-3 composite ceramics facilitates the production
of large-area, high-frequency sonar receiver arrays with good spatial and
angular resolution and wide angular cover, and a typical system with 200
staves each quantised to 18-20 bits and processed in the frequency band
100-200 KHz can provide beams 1° wide over ±80°.
However, replica correlation must be provided on each beam output for
target detection, followed by overall feature extraction and image
display, and the aggregate processing load presented by such real-time
data acquisition, processing and display is high. Hardware throughputs as
high as 5×1010 arithmetic operations per second may be needed
just to implement basic time-domain digital signal processing (DSP)
algorithms in real time. Substantial additional processing is required in
relation to data acquisition for signal conditioning, band definition and
data communications, and in practice the beamformer may need as well to
perform dynamic focusing in both range and bearing in order to minimise
echo smearing, and these additional processing functions may increase the
DSP processing load by several orders of magnitude.

[0004]The electronic noise floor from sensor arrays as above falls well
below the ambient acoustic noise floor in the ocean over the frequency
bands of interest, whilst maximum signal levels are determined by the
transmit source level of the system. To support both extremes it is
necessary to handle dynamic ranges in excess of 100 dB so that highlight
structure details (and hence the ability to classify them) of close-in
bottom features are maintained. It follows that the data acquisition
problem in high frequency imaging sonar systems is particularly acute.

[0005]In a paper entitled Wide band, high resolution sonar techniques
presented at an IEE Colloquium (Ref No 1998/217) in 1998, I and
colleagues discussed the problem of handling the high processing load
demanded by large aperture sensor arrays with wide processing bandwidths
required to resolve difficult targets and outlined possible solutions,
for both planar and conformal arrays, based on FDFT techniques.

[0006]The conformal arrays we considered at that time were those used as
flank arrays on submarines. These had a relatively small amount of
curvature in the vertical and were planar in the horizontal direction.
Because they were planar in the horizontal, with only limited curvature
in the vertical, the array beamforming is separable, i.e. we could use a
vertical beamformer on each individual stave of the confromal array, and
form for each stave a fan of vertical beams. Then, for each vertical
depression angle in each stave, we used a horizontal beamformer to form
the full horizontal beams. The vertical beamformers (which because the
number of elements in each stave were relatively small) were relatively
simple and were performed using space/time beamforming techniques I had
described previously in Space-Time Beamforming Using Recursive
Interpolation, Proceeding of the Institute of Physics, Conference on
Sonar Signal Processing, Loughborough, December, 1989. The horizontal
beamformers, which were more complex because the number of staves in the
array was large, used FDFT techniques.

[0007]For each array element we calculated a 64 k point FFT to get into
the frequency domain. The fractional FFT beamforming algorithm was then
implemented using a 256 point complex fast convolution across the
elements for each frequency cell. This process generated frequency domain
data, so we could implement fast replica correlation using a 64 k point
vector multiply on each beam output, followed by a 64 k point IFFT for
each beam to get back to the time domain.

[0008]This process is shown diagrammatically in FIG. 4 of the 1998 paper
and the flow is FFT, FDFT, Vector Multiply, IFFT.

[0009]It is an object of the present invention to provide improvements
upon the FDFT-based approach of Wide band, high resolution sonar
techniques, ibid.

[0010]Those skilled in the science will appreciate that the wide bandwidth
and large dynamic range rules out the use of commercially available
components for data acquisition. However, techniques based on the use of
custom band-pass delta-sigma converters allow the data acquisition
problem to be solved, as will now be outlined.

[0011]A low-pass sigma-delta converter was described by Boser and Wooley
in The Design of Sigma-Delta Analog-to-Digital Converters, IEEE Jour
SSC-23, December 1988. This converter comprises a three-port noise
shaper, an analogue-to-digital converter (ADC), a digital-to-analogue
converter (DAC) and a digital decimator/filter. The noise shaper is an
analogue circuit configured and arranged so that the forward gain in the
band of interest is very high. Thus quantisation noise introduced by the
ADC is reduced at the output by the loop gain of the converter (in much
the same way that output distortion is reduced in an operational
amplifier by heavy negative feedback). In the converter, the oversampled
ADC output data is filtered and decimated to select the required signal
band, and across this band the effective dynamic range is increased over
and above that of the basic ADC by the high loop gain and feedback action
around the noise shaper. Applications such as those of the present
invention require band-pass (that is, maximised effective dynamic range
in a band of frequencies remote from dc) rather than low-pass noise
shaping, and this can be achieved by first providing a low-pass noise
shaper with the required bandwidth and then applying regular analogue
filter low-pass to band-pass transformation techniques.

[0012]There is a possible secondary problem here. The ADC/DAC combination
must be oversampled to maintain Nyquist stability around the loop, and in
order to limit data transfer bandwidth some digital signal processing
(DSP) is needed in the region of the converters to band-shift the element
data and generate base-band signals that are oversampled no more than
necessary. Those skilled in the science will be aware of various
techniques to realise the band-shift/decimate process if the fractional
bandwidths are small. The wider bandwiths required here call for
techniques based on a combination of low complexity digital filtering,
sparse multipliers and digital noise shaping.

[0013]Beamforming and detection processing in sonar surveillance systems
must be able to provide sustained real-time throughputs to match the
digitised element data rate. Beamforming based on space-time
interpolation, as described for instance by Pridham and Mucci in A Novel
Approach to Digital Beamforming, JASA, 63(2), 1978, results in an
unacceptably high level of processing: for say an array of N=200
elements, with each beam needing 10×N arithmetic
(multiply-accumulate) operations, to form upward of 200 beams (to provide
reasonable angular cover) leads to an aggregate processing load in excess
of 5×1010 operations per second. Then, with typical current
DSP processors running at around 500 MHz, as many as 100 processors would
be required.

[0014]Accordingly some means of reducing the processing load is called
for. One possibility that may be considered is to use a 2D-FFT
methodology instead of Pridham and Mucci's time domain approach. This has
the potential to reduce the processing load by a factor of N2: N log
N, but at the cost of additional complexity. Even with a planar array,
2D-FFT beam outputs have a maximum response axis (MRA) that is a function
of frequency. The standard 2D-FFT beamformer maps from element-space to
k-space rather than to beam-space, and as a result it usually has to be
followed by interpolation (typically using a finite impulse response
filter, 2D-FIR) to provide further mapping from k-space to beam-space.
This produces beams that approximate those of an equivalent time domain
beamformer insofar as the MRAs are invariant with frequency and the
beamwidths decrease with frequency. But in practical terms the additional
interpolation commonly results in a processing load as heavy as that of
the time domain approach.

[0015]Because the discrete Fourier transform (DFT) is based on the
integral roots of unity exp(-j2π/N), all FFT calculations are
constrained to travel around the unit circle in the s-domain. However the
2D-FFT algorithm can be modified to allow arbitrary integration paths in
the s-domain, and thereby to map directly into beam-space, by defining a
fractional Fourier transform based on the fractional roots of unity
exp(-j2π/N(α), where α is arbitrary, as outlined by Bailey
and Swartztrauber in The Fractional Fourier Transform and Applications,
SIAM Review, Vol 33. September 1991. This fractional DFT (FDFT) can be
implemented using Bluestein's Decomposition, as outlined in A Linear
Filtering Approach to the Computation of the Discrete Fourier Transform,
IEEE Trans Audio Electroacoust, Vol 18, 1970. Bluestein's Decomposition
permits the computation of the FDFT by re-expressing it as a convolution,
which can be implemented using a fast algorithm with complexity
approaching that of the FFT algorithm.

[0016]The replica correlation processing load can also be reduced by use
of a fast frequency domain implementation. As the beamforming process
requires time-to-frequency domain and frequency-to-time domain
transformations, the replica correlation process can be wrapped up into
the beamforming process.

[0017]Reconciliation of the different requirements of sonar surveillance
has resulted in prior systems that are large and expensive and demand
substantial power supplies. But in many locations both space and power is
restricted; and the widespread deployment of surveillance systems needed
to cover the very large number of vulnerable locations noted above calls
for cost reduction.

[0018]It is a further object of the present invention to meet the various
requirements of sonar surveillance within limitations of cost, power and
space and thereby provide an underwater surveillance system that can
affordably be deployed in a large number of locations.

[0019]Thus according to the invention there is provided an underwater
surveillance system including:

[0020]a sensor array subsystem configured and arranged for immersion in a
body of water to transmit and receive sonar signals and comprising a
plurality of piezoelectric elements arcuately spaced apart azimuthally
around an angle θ;

[0023]characterised in that the beamforming subsystem is operative to
process outputs of the sonar array subsystem by means of a
pseudo-circular convolution technique thereby to form defined beams.

[0024]It will be noted that, in contrast with the approach of Wide band,
high resolution sonar techniques, ibid, the present invention provides
beamforming by means of a circular convolution with the array wave
function, rather than an FDFT beamforming algorithm.

[0025]The beamforming subsystem preferably includes replica correlation
processing operative by fast convolution of complex blocks of data from
each element of the sonar array subsystem to form multiple receive beams.

[0026]Preferably the data acquisition subsystem comprises multiple
continuous-time band-pass sigma-delta noise shaping modulators using
multibit feedback architecture and decimated finite impulse response and
wave digital filter (WDF) sections. The WDFs provide the main filtering
function in the signal flow, and it is further preferred that they
provide out of band rejection of greater then 120 dB, with in band ripple
less than 0.1 dB and with a pass band to stop band transition bandwidth
less than 4 kHz. Preferably, also, the data acquisition subsection
dissipates less than 150 mW per channel whilst maintaining 20-bit
precision.

[0027]Preferably the sensor array is circularly arcuate in azimuth, and
θ may be 360°.

[0028]The sensor array may be divided into a plurality of sectors
configured and arranged to provide a specified azimuthal spread, and each
sector may have an angular dimension of 45° in azimuth.

[0029]The sensor array preferably comprises a 3-1 piezo-composite material
impedance matched to the water. To provide the arcuate array the
piezo-composite material may be curved by a kerfing process entailing
preferentially cutting wider kerfs between the active transducer areas.

[0030]Preferably the multiple receive beams are azimuthally narrow, so
that the system provides high angular resolution. For instance, the
azimuthal beamwidth of each beam may be 1°. The elevational
beamwidth of each beam may be 10°.

[0031]The system preferably operates at about 100 kHz and the sonar array
has dimensions of about 850 mm horizontally and 100 mm vertically.

[0032]The block processing function preferably comprises the steps of (a)
transforming the time-domain data block into a plurality of cells in the
frequency domain by means of a 64 k point fast Fourier transform (FFT),
(b) fast replica correlation by means of 64 k point vector multiplication
of each of the frequency domain data block outputs, (c) fast convolution
by means of a 512 point complex fractional FFT or pseudo-circular
convolution implemented across the elements for each frequency cell,
thereby to generate frequency domain beam data, and (d) 64 k point
inverse FFT (IFFT) to return to the time domain.

[0033]The data acquisition subsystem preferably includes digital filtering
and decimation, which may be implemented in field-programmable gate array
(FPGA) form.

[0034]The underwater surveillance system preferably includes a power
amplification subsystem operatively connected to the sensor array
subsystem and configured and arranged to deliver thereto at least 215 dB
relative to μPa at 1 m.

[0035]The system preferably includes a detection processing system
operatively connected to the beamforming subsystem and configured and
arranged to extract intruder echo data from noise and reverberation.

[0036]The system preferably includes a display processing subsystem
operatively connected to the detection processing subsystem and operative
to define tracks from the intruder echo data.

[0037]The system preferably includes a display subsystem operatively
connected to the display processing subsystem to display intruder images
and tracks.

[0038]Other features of the invention will be apparent from the following
description, which is made by way of example only with reference to the
accompanying schematic drawings in which--

[0039]FIG. 1 illustrates the geometry of a cylindrical array of sensors B;

[0040]FIG. 2 illustrates, for the array of FIG. 1, a complex array wave
function for a source at broadside;

[0041]FIG. 3 illustrates, for the array of FIG. 1, complex array wave
functions for a source rotated in 30° increments from broadside
through to broadside;

[0048]FIG. 10 summarises key parameters for an underwater intruder
detection system according to the invention, which parameters are derived
from detailed modelling of the system and a harbour/port environment;

[0049]FIG. 11 illustrates a sector of a sensor array;

[0050]FIG. 12 shows a plurality of sectors as in FIG. 11 assembled
together to form a cylindrical sensor array;

[0051]FIG. 13 is a top-level block schematic illustration outlining a
surveillance system according to the invention;

[0052]FIG. 14 is a more detailed block schematic illustration of the
system showing multiple array elements;

[0053]FIG. 15 is a block schematic illustration distinguishing the wet end
(in the water) from the dry end (out of the water);

[0054]FIG. 16 illustrates filtering, bandshifting and decimation in a
system according to the invention;

[0055]FIG. 17 illustrates beamforming and signal processing in a system
according to the invention;

[0056]FIG. 18 illustrates a display taken from a test of a system
according to the invention showing detection of a diver equipped with
closed circuit rebreather SCUBA at a range of about 800 m;

[0057]FIG. 19 illustrates a display like that of FIG. 12, showing the
diver at a range of about 300 m; and

[0058]FIG. 20 illustrates a display showing the track of the diver from
the position of FIG. 18 to that of FIG. 19.

[0059]A beamformer equation for producing a beam in a particular direction
from an array of sensors can be written as:

A r ( t ) = k = 0 N - 1 S k B k ( t +
τ r , k ) ( 1 ) ##EQU00001##

[0060]where [0061]Ar(t) is the beamformer output for the rth
beam in a fan thereof. [0062]Sk is the array weighting function
applied to the kth sensor [0063]Bk (t) is the time domain
signal received at the kth sensor [0064]τt,k is the time
delay applied to the signal from the kth sensor to form the rth
beam in the fan.

[0065]For a cylindrical array of sensors B as shown in FIG. 1, the
compensating time delay, τr,k, for a beam r pointing to the
right as seen in FIG. 1 can be derived from the geometry as:

τk=R/csin(θk) (2)

If Bk(t) is a narrowband process, corresponding to some frequency
ω, we can express the beamforming operation as a phase delay,
rather than a time delay process, in the form:

[0066]The equivalent phase delay for the cylindrical array configuration
can be expressed as:

exp(jφk)=cos(R/csin(θk))+j sin(R/csin(θk))
(5)

[0067]In practice, the elements themselves have some defined horizontal
beam pattern that modifies the spatial extent of the "wave function"
chirp. This may be due to the way the transducers are mounted onto the
array structure or it may be due to the actual design of the element
itself. In the limit, for a typical system where the array mounting forms
an acoustic baffle, the element response could extend though
±90°. Applying this ±90° constraint and plotting
Equation (5) above for an array with a moderate number of transducers and
with linear spacing less then λ/2 at frequency ω, reveals
phase compensation in the form of a complex spatial chirp, as indicated
by FIG. 2.

[0068]Moving a source around the array, the spatial chirp (or the array
"wave function") remains the same shape but rotates around the array in
sympathy to the source rotation. That is to say, the shape of the wave
function is rotationally invariant. However the null position of the
chirp indicates the direction of the source, as illustrated in FIG. 3 for
a source rotated in discrete 30° increments around the array. It
follows that, by generating this phase correction chirp and applying it
to the array element data to form a beam, additional beams can be
produced by rotating the same chirp function around the array and
calculating the beam summation defined by equation (4) for each required
direction.

[0069]This process effectively calculates the circular convolution of the
wave function chirp with a snapshot of the narrow-band array data. The
mathematical properties of this convolution process can be used to
simplify the practical implementation of the beamformer, as will now be
discussed.

[0070]It is well known that circular convolution in the time domain is
equivalent to vector multiplication in the frequency domain. Therefore it
is possible (a) to transform a snapshot of the N array element time
domain data samples into the frequency domain, using an N-point discrete
Fourier transform (DFT), (b) to transform the N-point phase chirp into
the frequency domain, again with an N-point DFT, (c) multiply the two
resultant frequency domain vectors pointwise together, and then (d)
transform the resulting N-point product vector back into the time domain,
using an N-point inverse DFT. This generates a snapshot of a fan of N
time domain beams. This process can be performed on successive snapshots
of the array data, taken at some sample rate faster then the Nyquist
rate, to form a continuous time series of the beam formed data. See
Farrier et al in Fast Beamforming Techniques for Circular Arrays, J
Acoust Soc Am, Vol 58, No 4, October 1975 and DeMuth in Frequency Domain
Beamforming Techniques, XXX, 1976

[0071]A problem with implementing the above algorithm as a low complexity
beamformer is that the transform length, N, has to match the number of
elements in the array, and the manipulation generates a fan of N beams.
This process can be carried out efficiently if the number of elements and
beams is given by 2n, for example when there are 256 or 512 elements in
the cylindrical array, when the DFT and inverse DFT can be calculated
using Fast Fourier Transform (FFT) techniques. Unfortunately, in many
practical applications, the constraint N=2n causes other problems:
for example, it is convenient to use an element spacing in the array
equal to 1°, giving N=360, but this length transform cannot be
calculated directly using the FFT.

[0072]However, the DFT block length N (360 in the above problematic
example) can be rewritten as the product (8×9×5), allowing
implementation of the 360-point transform using cascaded small length
DFTs, ie of lengths 8 points, 9 points and 5 points. This can be achieved
using decomposition detailed by Good in The Interaction Algorithm and
Practical Fourier Series, J Roy Statist Soc, Ser B, Vol 20, 361-372,
1958, to partition the matrix processing into three distinct passes and,
as the small DFT block lengths are relatively prime, use the Chinese
remainder theorem, (first detailed in Sun Tzu Suan Ching circa 300 AD) to
minimise the amount of calculation required, by eliminating the
inter-pass twiddle factor multiplications.

[0073]The foregoing approach has been used in both custom hardware and
FPGA based implementations, using low complexity transform techniques
detailed in Spreadbury and Curtis in International Patent Application
WO87/07053, the contents whereof are hereby imported by reference. This
provides cost-effective solutions for stand-alone, battery-powered
underwater intruder detection systems intended for portable expeditionary
deployment.

[0074]However, for more general and widespread use in harbour and port
protection, it is preferable to perform all the beamforming and signal
processing on an inexpensive and generally available personal computer
(PC). Whilst the address sequence complexity required to code small
length relatively prime transforms comes for free using the massive
interconnection resources available on FPGAs, this becomes a prohibitive
overhead when such algorithms are mapped onto PC CPU cores. It is
therefore necessary to find a way to implement these circular
convolutions using standard library calls to efficient FFT routines, in
order to implement these algorithms efficiently on current generation
commercial CPU cores. By this means the invention can provide a low cost,
compact sonar surveillance system capable of protecting high value
targets from assymetric attack by swimmers, divers and the like.

[0075]Consider an array in which the transducer elements are angularly
spaced apart at 1° intervals. For the maximum system
configuration, we use a fully filled cylindrical array, with nominally
360 transducers (although some of these are interpolated data where
elements between the 45 degree sector arrays are of necessity omitted as
will be explained in more detail hereinafter).

[0076]It is necessary to map these 360 channels of element data
efficiently onto a set of standard high performance primitives that
support efficient realisation of signal processing functions on current
generation desktop CPU cores. In short, the system has to support 360
point circular convolution on a 512 point FFT.

[0077]Two practical solutions to this problem are element space
interpolation and pseudo-circular convolution, each of which
possibilities will now be discussed in turn.

[0078]First, with regard to element space interpolation, the 360 element
cylindrical array data can be spatially interpolated to generate what is
effectively a 512-point cylindrical array. This interpolation itself can
be organised in several ways, either using a sparse spatial FIR or by
using wave digital filter (WDF) interpolation.

[0079]Typically, for the spatial FIR interpolator, it is necessary to
calculate an 8 point interpolation for each of the 512 output data
points, requiring just one pass through the data and using 4096 complex
multiplies and adds (equating to 16384 real multiplies and 8192 adds).

[0080]With the WDF approach, all pass sections can be arranged to provide
interpolation ratios given by some integer value, e.g. ×2,
×3, etc. Thus the minimum sized integer interpolation/decimation
ratios that can be implemented in this way are an (interpolate by
64)/(decimate by 45) function: that is, the integer fraction 64/45
represents the LCM quotient/divisor that can be supported. This 64/45
interpolation ratio is most conveniently implemented by a factoring
process as follows using: [0081]interpolation by 64=4×4×4
[0082]and decimation by 45=3×3×5.

[0083]Hence, the interpolation/decimation process flow can then be
interleaved, to minimise the process steps, as: [0084](A) Interpolate
by 4/decimate by 3 [0085](B) Interpolate by 4/decimate by 3 [0086](C)
Interpolate by 4/decimate by 5

[0087]The interpolate by 4 process can itself be reduced to two cascaded
interpolate by 2 processes and then the complete process reduces to a
continued application of an identical interpolate by two process,
interspersed at intervals by a decimation, which simply requires a data
selection process. For example, to decimate by 3, save only every
3rd point from the interpolators, and discard all other samples. For
decimation by 5, only every 5th point is saved.

[0088]It follows that the interpolate by 2 process is the only operation
that requires arithmetic number crunching. It can be realised effectively
using a WDF structure using just one binary shift and two add operations
per interpolated data point, so it is a very low complexity process. The
interpolate function is performed using all pass WDF sections, which each
generate an interpolated data point, as I described in Space-Time
Beamforming Using Recursive Interpolation, ibid.

[0089]The above process is illustrated schematically in FIG. 4, together
with the z-domain transfer functions generated.

[0090]Overall, the process requires three passes through the element data
to complete the full interpolation processing, requiring a total of 23680
adds.

[0091]For both FIR and WDF, the resultant 512-point effective array is
forward transformed, multiplied by a transformed replica of the array
wave function, and inverse transformed to generate a fan of 512
contiguous beams. The complete process is then repeated for each
frequency cell in sequence in the 64 k cell spectral data block.

[0092]Pseudo-circular convolution involves modifying the data address
sequence that transfers the 360-points of element data into the 512-point
FFT input buffer store, so that the data points are themselves organised
to repeat modulo 360 in the buffer. Then it is possible to select just
that part of the 512-point circular convolution that provides an
unambiguous 360-point circular convolution. This is achieved as follows.

[0093]First, consider by way of example a cylindrical array of P
transducers, from which it is wished to form a fan of P beams, using an
arc of the array comprising Q hydrophones. The wave function examples
considered above to illustrate the circular convolution approach to
cylindrical array beamforming used an arc length equal to P/2 elements.
If this arc length is to maintained, then in order to obtain a true
circular convolution from a non-P point FFT, it would be necessary to use
an FFT length, N, greater than (P+P/2). Thus the case of P=360 demands an
FFT length greater than 540, i.e. an FFT block length, N=1204. However,
as noted previously herein, in a practical array the actual arc length
possible is a function of the horizontal beam shape of the individual
array elements.

[0094]Thus the minimal size FFT that could support a 360-point circular
convolution leads to an inequality:

(360+Q)<512

or

Q<152

[0095]Accordingly, if the natural beam shape of the individual transducer
elements in the array is contained within 152 degrees of azimuth, it is
possible to use a 512-point FFT to calculate a 360-point circular
convolution. In practical 1-3 composite arrays, this constraint is
usually met, as the requirement for a λ/4 matching layer to
maximise energy transfer between the array and the medium results in
azimuth beamwidths typically well contained within 152°, as shown
in FIG. 5.

[0097]The beamforming process is then organised into four stages as
follows: [0098](a) (a) The 360-points of element data defining data
from elements 0 through 359 are written to locations 76 through 435 of
the 512-point FFT input buffer. The data from elements 0 through 75 is
then repeated in locations 436 to 511 of the buffer and data from element
283 through 359 in buffer store locations 0 through 75 (i.e. the buffer
store is loaded with element data using an address sequence calculated
modulo 360, as shown in FIG. 8). Logically this process can be described
by the algorithm:

TABLE-US-00001
[0098] For count:=0 to 511 do
Buffer[count]:=Element[(count+283) mod 360)]

[0099](b) The 512-point complex data block in the buffer is forward
transformed using a 512-point FFT algorithm. [0100](c) The resultant
vector is multiplied pointwise with a transformed version of the wave
function. (This is generated off line, by padding the 152-point complex
wave function data with 360 zeros, as illustrated in FIG. 9, and forward
transforming that vector). [0101](d) The 512-point complex vector product
is inverse transformed and the first 360 points of the vector that
represent the unambiguous circular convolution are selected.

[0102]The process has been described above for P=360 and Q=152, but those
skilled in the science will appreciate that it can be generalised for
smaller values of Q if required.

[0103]Other methods may also be used to support 360 point circular
convolution on a 512 point FFT. The beamforming algorithm described above
in relation to pseudo-circular convolution is efficient in that
application if and only if Q≦152. If Q>152, then it is
necessary either to migrate up to the next available FFT size (ie to 1024
points) and accept a loss in efficiency or to use a fractional FFT
algorithm to allow direct implementation of 360-point circular
convolutions by means of Bluestien's Correspondence to implement these
using 512 point FFTs. The relative efficiency of this vis-a-vis the
1024-point transform approach is dependent on FFT efficiency.

[0104]Target echo highlights seen from a swimmer are generated mainly by
reflections from internal air cavities such as the lungs and other body
cavities, from exhaled air bubbles and from compressed air tanks where
SCUBA is used. These highlights show up best using frequencies around 100
kHz.

[0105]Harbour surveillance systems must be able to detect intruders in
reverberant conditions, such as the cluttered shallow water environments
normally encountered in harbours and the like. This requirement leads to
a design using narrow receive beams with wide frequency bandwidth centred
around 100 kHz, and the use of large bandwidth×time (BT) product
coded transmissions, to combat the effects of reverberation and detect
targets against the reverberant background. As well as providing good
angular resolution on receive, it is necessary to ensure a wide angle of
cover to detect threats coming from all directions. This requires an
omni-directional transmit system that supports wide bandwidth, high BT
coded pulses and a receive system that generates a fan of contiguous
narrow beams to detect against the low target strength targets against
the reverberant background. This requirement for omni-directional
transmission, with a narrow beam receive system leads to the use of a
cylindrical array topology as the natural "geometry of choice" for such a
system. Such a cylindrical array would comprise a plurality of vertical
staves with essentially an omni-directional response in the azimuthal
(horizontal) axis but with some defined directivity in the elevational
(vertical) axis.

[0106]The surveillance system must provide sufficient warning time when
intruders are detected, to allow time for countermeasures to be deployed.
For a typical attack swimmer, using a covert closed cycle rebreathing
apparatus, and swimming at an average speed of say 0.25 m/s to 0.50 m/s,
a 30 min alert time demands that intruders be detected at a range between
450 m and 900 m.

[0107]Those skilled in the science will also appreciate that, as well as
the normal spreading losses that occur when acoustic waves travel through
water, there are additional losses due to absorption effects. These
absorption losses are a strong function of frequency and severely limit
the possible detection ranges in high frequency sonar systems. For
example, absorption loss is typically around 30 dB/km at 100 kHz, rising
to around 100 dB/km at 300 kHz. For a typical detection range of say 800
metres, therefore, absorption loss will be around 50 dB at 100 kHz,
rising to around 170 dB at 300 kHz. It follows that the working frequency
of 100 kHz which provides the best target echo highlights as noted above
also provides favourable absorption loss in comparison with higher
frequencies.

[0108]Using the basic parameters outlined above for detection range and
sonar characteristics, together with typical values for intruder target
strength, allows predicted sonar performance to be modelled for various
sonar configurations and selection of a system configuration that is well
matched to the basic performance requirements.

[0109]The predicted performance of a system using a 360° 1-3
composite array was modelled for a harbour environment by means of
simulation software. The results are shown in FIG. 10, which shows
calculated propagation loss budget and detection range for a source level
of 220.4 dB and a transmit pulse rate of 2 s. FIG. 10 lists array and
sonar parameters, sonar equation parameters and estimated performance
figures. On the basis of this modelling, a receive array of the order of
850 mm diameter and 100 mm height, capable of supporting high transmit
source levels using high BT product coded transmissions, can provide the
required level of surveillance over 360° up to a range of between
990 m and 1120 m. The average supply power is 184.8 W.

[0110]The development of a practical underwater surveillance system from
the model parameters of FIG. 10 will now be discussed, beginning with the
array technology.

[0111]In a sonar array for a system according to the present invention,
with the frequencies and bandwidths indicated, it is necessary first of
all to choose between polyvinylidene fluoride (PVDF) polymer and ceramic
piezo-composite technology. (Whilst it is possible to produce sensors
using arrays of conventional miniature transducers, the
transducer-to-transducer matching that can be achieved in this way is
nowhere near as good as that produced by the batch production techniques
used with either PVDF or piezo-composite. Also the costs in
"hand-crafting" very small individual hydrophones are excessive. The need
for wide bandwidth from the array militates against the use of a
conventional piston based design, because evaluation has shown that it is
difficult to provide a bandwidth approaching 20 kHz at a 100 kHz centre
frequency with this form of transducer).

[0112]From assessment of prototype arrays, PVDF appears to offer a low
cost solution, but the technology is at this time somewhat immature.
Further, trials of PVDF suggest there may be problems in de-poling of the
polymer at elevated operational temperatures and also problems with
producing viable source levels.

[0113]By contrast, piezo-ceramic technology has been well proven over 30
years or more and is commercially available from a variety of sources.
Accordingly a piezo-ceramic array is preferred herein (although it should
be noted that this preference is not a limitation on the present
invention, which is defined by the claims set out hereinafter).

[0114]To minimise cost in the present invention, the same array is used
for both transmit and receive. This leads to a number of refinements in
the base technology to provide a large cylindrical array that can support
source levels in excess of 220 dB re uPa @ 1m, with bandwidths of 40 kHz
or more centred on 100 kHz, whilst maintaining high receive sensitivity.

[0115]An array meeting a basic specification derived from the sonar system
modelling is available from Alba Ultrasound Limited of Glasgow, UK. An
array manufactured by them and used in the invention comprises a
plurality of 45° sector modules that can be assembled contiguously
to provide a full circle (and can also, by selective operation, provide
angular cover from say 90° degrees to 360°. This modular
arrangement allows more flexibility than an integral 360° array.

[0116]FIG. 11 shows two views of a 45° sector module 10,
respectively from the front (that is, showing the arcuate,
outwardly-directed face 10a of the module 10) and from the rear (which
has a substantially planar face 10b). The vertical dimension of the
module is about 100 mm, and the arcuate front face 10a is about 340 mm
long along the arc.

[0117]Referring now to FIG. 12, eight modules 10 of the kind shown in FIG.
11 are assembled together side-by-side to form a full 360° array
indicated generally at 12. (The forward one of the modules 10 as seen in
FIG. 12 is drawn out of the circle to show that it comprises a slice of
the complete ring). Each module 10 has an angular dimension
θ=45° and a vertical dimension h≈100 mm. The whole
array 12 has an overall diameter d≈850 mm.

[0118]Whilst each module 10 has an angular dimension of 45°, in
fact it comprises 44 sensors each having a wide beamwidth in azimuth (and
10° in elevation) angularly spaced apart at 1° increments.
This is because physical limitations make it necessary to omit one sensor
per module (i.e. 44 sensors instead of 45) to provide space to
accommodate the array housing. However, the effect of the omitted
elements can be compensated in the sonar signal processing electronics to
minimise the effect on the sonar beampattern.

[0119]Acoustic tank measurements show that the array module 10 provides
the 44 elements with individual gain and phase matching within 0.5 dB and
2° rms respectively, and that the module 10 can support in excess
of 40 kHz bandwidth and also provide source levels in excess of 220 dB.

[0120]Moving on now to signal processing, an elementary schematic for
implementing the required signal processing flow is shown in FIG. 13. (It
should be pointed out that this schematic is very general, and by no
means unique to the present invention, but it will nevertheless help the
invention to be understood).

[0121]Insofar as the array comprises a plurality of 45° sector
modules, it is convenient for the electronic processing components needed
in close proximity to the array to be similarly quantised. That is to
say, the electronics processing data in the "wet end" of the system is
configured and arranged to map on to the modular structure of the array
itself, with 44 elements spread over 45°.

[0122]It is also preferred to minimise the amount of electronics needed in
the wet end of the system and to perform as much as possible of the sonar
processing at the surface (in the so-called "dry end"). The processed
data from the array modules are combined in a central hub that supports a
wide band fibre optic umbilical link cable for data transmission and
control to and from the dry end. The hub also provides power line
conditioning, from the copper power feed contained in the umbilical, to
provide dc power to the wet end electronics. This wet end/dry end split
minimises the overall system cost and allows maximum flexibility in
providing various configurations of the system for disparate operational
deployment scenarios.

[0123]FIG. 13 provides an overview of an underwater surveillance system
according to the invention. At the heart of the system is an underwater
sensor array 20 comprising a plurality of sensor elements which both
transmit and receive acoustic signals. Power amplifiers 22 generate
electric transmit signals which are converted to acoustic form for
transmission by the sensor array 20. Incoming acoustic signals, including
echo data from any intruder in the water, are received by the sensor
array 20 and passed to a data acquisition subsystem 24, which digitises
the data for processing. The digitised data is passed to a beamforming
subsystem 26 which forms defined beams from quasi-omnidirectional element
data. A detection processing subsystem 28 then extracts signals from
noise and reverberation and passes these to a display processing
subsystem 30 which defines tracks from the intruder echo data. Finally,
intruder images and tracks are displayed by a display subsystem 32.

[0124]The wet end processing module is as shown in the schematic in FIG.
14. The electronic circuits defined in this schematic were manufactured
in the form of a compact unit that mounts directly behind the array
module, to minimise the inevitable electronic noise and interference
inherent in such compact devices.

[0125]Referring now to FIG. 14, this shows an array module 10 (like that
shown in FIGS. 11 and 12) in juxtaposition to an associated electronics
assembly 40. The array module 10 is equipped with forty-four hydrophone
elements 111, 112 . . . 1143 and 1144. The
electronics assembly 40 a transmit unit 42, a preamplifier unit 44 and an
ADC and filter unit 46.

[0126]In the transmit unit 42 a power conditioning and DC link converter
48 receives power input and control I/P and delivers DC power to the ADC
and filter unit 46. DC power is in turn delivered from the ADC and filter
unit 46 to the preamplifier unit 44. The transmit unit also includes a
transmit waveform generator and power amplifier 50 which delivers
transmit and Tx signals T to the preamplifier unit 44.

[0127]The transmit and Tx signals are fed to forty-four T/R switches
521, 522 . . . 5243 and 5244, one for each of the
hydrophone elements 111 to 1144, each with an associated
preamplifier 541, 542 . . . 5443 and 5444. The
preamplifiers 541 to 5444 feed respective ADCs 561 to
5644 in the ADC and filter unit 46 The ADCs 561 to 5644
feed respective switch gain compensate devices ADCs 581 to 5844
which are in turn linked by 24 dB gain switch control 60 to the
respective preamplifiers 541 to 5444.

[0128]The switch gain compensate devices feed a common multiplexing,
filtering and decimation device 62. This device 62 delivers module output
O/P to signal processing (not shown in FIG. 14) and receives module
control MC from signal processing. To complete the control loop, the
multiplexing, filtering and decimation device 62 also delivers Tx control
TC to the power conditioning and DC link converter 48

[0129]FIG. 15 shows the hub/umbilical schematic. The processing is divided
between the wet end and the dry end indicated in broken lines at 70 and
72. The wet end 70 comprises eight array modules 101 to 108
interconnected with a hub data concentrator 74. In the dry end 72 a top
end interface 76 is interconnected with a sonar interface 78 and a cable
power interface 80 which receives power input I/P for the system. Also in
the dry end 72 a sonar DSP and display unit 82 is interconnected with the
sonar interface 78. The wet end 70 and the dry end 72 are linked by an
umbilical cable 84.

[0130]In more detail, the wet end of the system provides a number of
functions as follows.

[0131]First, the wet end includes a transmitter to provide the high BT
product transmit waveform. This is driven into all the sensor transducers
in parallel during the transmit period to provide an omni-directional
transmission from the 8 module system (or a transmit cover in increments
of 45 degrees for system using fewer modules). The power produced by this
transmit amplifier module is necessarily high, to provide the required
source level (up to 5 kW per module). To make sure that the transmitter
would work correctly with a high loop resistance power feed provided by
the umbilical, the power taken by the transmit system is spread
throughout the complete receive cycle (as outlined below), and the
umbilical is effectively isolated from the receive subsystem (to avoid
"frying" it) by logically interlocking the power amplifier control system
so that transmit signals can only be generated when the transmit/receive
switch is in a safe position, thereby isolating the receive circuits from
the transmit power chain.

[0132]The transmitter module itself provides a number of different
functions. The power for the module input is provided via a copper feed
from the umbilical, at a nominal 115 volts, 60 Hz. The front end of the
power amplifier implements a current limited charge pump that charges
local high density storage capacitors to provide a nominal 400 volt dc
link supply. The energy for the transmission is provided from these
storage capacitors, and these are trickle charged at the rate of around
0.5 amps between transmissions. This approach is used to spread the peak
power demand for the high power transmissions over the complete receive
cycle, thus allowing the use of much lower rated (and hence cheaper and
smaller) copper cable in the umbilical. The dc link supply feeds to the
power output stage, a conventional class D system using an H-bridge
topology, realised using third generation Insulated Gate Bipolar Devices
(IGBT) with silicon carbide reverse energy recovery diodes. This
combination provides a very high efficiency, rugged output stage. The
bridge output feeds to the transmit/receive switches via an L-C matching
network that minimises the imaginary part of the complex transducer load
impedance over the required frequency band, and hence maximise power
transfer to the array.

[0133]The transmit/receive switch (T/R switch) provides a path for the
transmit power to get from the power amplifier to the 44 individual
transducers during the transmit period. Also at this time it isolates the
receive system from the transducer to avoid overstressing the sensitive
front end pre-amplifiers with the large voltage needed for transmission
(around 1500 volt peak to peak). During the receive period, the T/R
switch connects the 44 individual transducers to their respective low
noise pre-amplifiers: the signal levels seen at this point are of the
order of a few tens of nano-volts. So, it can be appreciated that the T/R
switch has a major role in the system operation, needing to stand off up
to ±1 kV during transmission whilst passing a signal level of a few
tens of nano-volts during the receive period.

[0134]The pre-amplifiers interface to the essentially capacitive
transducer source and provide a low noise charge amplifier scheme to
amplify the received signals to sufficient level to feed the following
analogue-to-digital converters (ADCs). The pre-amplifiers provide a
switched gain circuit that is controlled from the surface electronics, to
allow the system gain to be modified during the receive period, if
necessary. The pre-amplifier circuits also contain an inject facility
that allows test signals to be injected, on command from the top system
electronics, into the analogue data path close to the front end of the
system to check out system performance in real time. This allows the
operator to perform system confidence checks and to determine the state
of the particular transducers in the array. The inject Built In Test
(BITE) system provides the input to allow the signal processing software
to compensate for failed or faulty channels.

[0135]The ADCs convert the analogue signals from the preamplifiers into
digital signals for signal processing. The ADCs use a proprietary
continuous time, heavily over-sampled noise shaping modulator to provide
a large dynamic range with minimal hardware complexity. This approach was
used instead of design using "off the shelf" silicon integrated circuits
in order to minimise the system power whilst at the same time maintaining
adequate system dynamic range. The ADCs basically quantise the signal
data at a 20 MHz rate, using an 8-bit word length. The noise shaping is
used to shape the quantisation noise spectrum in order to maximise the
signal to quantisation noise across the receive band. This band is then
filtered out in the following signal processing, to provide signals with
a nominal 20 bit resolution data in band.

[0136]Considering now filtering, bandshifting and decimation, the signals
from the 44 individual ADCs in each electronics module feed to a
collection of Field Programmable Gate Arrays (FPGAs). The four FPGAs per
module each process 11 transducer channels and are configured by firmware
to carry out the necessary filtering process to extract the high
precision data in the receive band from the over-sampled data from the
noise shaping modulators. The signal flow used for this process is shown
in FIG. 16. The 8 bit over-sampled data is first filtered and decimated
by a factor of 12 using a cascade of decimated finite impulse response
(FIR) filters. The decimated data, now at a 1.6667 MHz sample rate with a
word length of 17 bits is then multiplied by a complex bandshifting
sequence to base-band the data. The resultant complex (i.e.
real/imaginary) bandshifted data is further decimated by a factor of 8
using decimated FIR filters. This data is further processed by a cascade
of two proprietary Wave Digital Filter (WDF) sections, that produce 24
bit complex data at a 52.08333 kHz complex sample rate. The WDFs provide
the main filtering function in the signal flow, they provide out of band
rejection of greater than 120 dB, with virtually no in band ripple and
with steep pass band to stop band transition. WDF filters were chosen as
they provide the most efficient high performance filtering mechanism,
being a factor of 5 more efficient than other known solutions.

[0137]Suitable WDF techniques are outlined in United States Patent
Application US 20050050126, which describes digital signal-processing
structure and methodology featuring a time-slice-based digital
fabricating engine, and software operating structure operatively
associated with that engine structured to operate the engine in a
time-slice-based fabrication mode wherein the engine, in a
time-differentiated and instantiating manner, functions to fabricate a
time-succession of individual, composite wave digital filters. Each of
these filters takes the form of (1) a concatenated assembly including one
to a plurality of upstream, early-stage, decimate-by-two,
signal-processing agencies connected in a cascade series arrangement,
with each such agency possessing a first transfer function having a first
transition bandwidth, and (2) a single, downstream, later-stage,
decimate-by-two, signal-processing agency which possesses a second
transfer function having a transition bandwidth which is less than the
mentioned first transition bandwidth.

[0139]The base-banded filtered complex data from the final WDFs form a
multiplexed data stream that contains the data from all elements in the
array modules. The data streams from each of the modules in the array
feed to the wet end hub subsystem, where they are combined and fed via a
1.25 Gbit/s fibre transceiver to the fibre umbilical cable, for
transmission to the dry end.

[0140]The low power electronics circuits are powered using commercial
power supplies that form part of the hub electronics, fed from the 115v,
60 Hz umbilical cable feed.

[0141]The umbilical cable is available from LEMO (UK) Limited of Worthing,
West Sussex, UK. It provides two separate 1300 nm, single mode fibres, a
copper pair for power distribution and a further copper pair that is used
to support a dedicated flood alarm system, to warn of any water ingress
in the system. Typically this umbilical cable is between 100 m and 1 km
in length, depending on where the sonar wet end is to be deployed.

[0142]The top end hub interfaces to the umbilical cable and receives the
optical data via a 1.25 Gbit/s fibre transceiver. The output from the
transceiver feeds to an FPGA system that is firmware programmed to
provide local storage of all the data received from the array during the
receive cycle, using high density DRAM stores. The FPGA also interfaces
to a USB interface that allows the top end computer to access the stored
received data and to send various commands to the wet end to cycle the
transmission, control the BITE inject sequence, set the system gain, etc.
The top end unit also contains the power interface, fed from an isolating
transformer, itself fed from a 115v, 60 Hz mains source. The top hub also
measures the variation of impedance of an inter-digitated flood sensor
mounted in the array enclosure to monitor for possible flooding in the
wet end system, sounding an alarm if flooding is detected.

[0143]The top end processing will now be discussed, first with reference
to beamforming and target echo processing.

[0144]Transducer data from the individual elements in the sonar array are
received from the 1.25 Gbit/s fibre optic umbilical via a transceiver and
fed to the top end hub processing, as described hereinbefore.

[0145]Data is stored locally in the hub for the complete receive period.
This data is stored element sequentially for each of the transducers in
the array, with sufficient samples stored to provide a reasonable
surveillance range bracket. For a system bandwidth of 52.08333 kHz, the
corresponding sample rate equates to 19.4 μs, so storing 64 k samples
provides a time series length of 1.258 seconds, equivalent to a
surveillance range bracket of around 930 metres, for a nominal speed of
sound in the water of 1490 m/s. This range bracket matches well to the
detection performance of the system. The time used to start gathering
these time history blocks can be offset by the operator. Thus, the usable
930 metres range bracket can, for example, be set to provide surveillance
cover extending 930 metres from the array or can be offset to provide an
annular surveillance range cover extending from X m to (X+930) m, where X
can be selected by the operator.

[0146]The 64 k complex samples for each transducer in the array are stored
in local SDRAM in real time as they are processed by the wet end
electronics. This received data is read across to a desktop PC, via a
USB2.0 interface, in non-real time, so the hub data store provides an
elastic buffer to allow for the asynchronous operation of the top and
bottom end processes. The data read by the PC via the USB interface is
stored in the PC memory as a 2-D matrix, with the 64 k complex time
samples stored in time order for each of the transducers in the array
sequentially. Data at this stage is 24 bit complex fixed point format and
the first signal processing operation is to convert the fixed point data
matrix to 32 bit complex floating point, to minimise truncation and
rounding effects in the downstream processing. The floating point data is
written back into a time-space matrix, with similar format to that
outlined for the fixed point data and the signal processing functions to
beamform the data and to extract target echoes performed. However, spare
slots are left in the 2-D matrix for the "missing channels" between each
array module and also any channels that test as faulty by the BITE system
are zeroed out.

[0147]An interpolation process is then carried out to approximate the data
values in the missing and faulty channels using a FIR spatial filter
across adjacent transducer signals. This interpolation process is
essentially a lumped, linear bilateral process and could therefore be
applied at a number points in the overall processing flow. It is
described here for convenience but could equally well be performed later
in the process flow, for example, in the frequency domain rather than in
the time domain as here.

[0149]As noted hereinbefore, the present invention provides beamforming by
means of a circular convolution with the array wave function, rather than
the FDFT approach of my 1998 paper Wide band, high resolution sonar
techniques, ibid. More particularly, the process flow of the present
invention is FFT, Vector Multiply, Circular Convolution, IFFT, which
contrasts with the flow FFT, FDFT, Vector Multiply, IFFT of 1998.

[0150]The signal processing operation uses a collection of time and
frequency domain processes. It wraps the correlation processing for echo
extraction around the frequency domain beamforming process in order to
minimise the overall processing load. The operation is as follows.

[0151](a) The 64 k complex floating point time series block for each
channel in turn is converted into the frequency domain using a high
performance proprietary FFT algorithm.

[0152](b) The complex frequency domain data vector for each channel is
multiplied by the complex conjugate, frequency domain version of the
transmitted pulse to perform a circular correlation of the received time
series data with the transmit waveform to extract echo data.

[0153](c) The resultant frequency domain correlated channel output vectors
are written back in place into the 2-D storage matrix.

[0154](d) The 2-D matrix is then addressed in the orthogonal direction
(i.e. corner turned) and the 360 complex frequency domain samples for
each of the 64 k frequency cells in sequence are fed to an FFT based
process that convolves the 360 samples of element data across the array
for that particular frequency cell with a frequency domain version of the
array wave function at that particular frequency, to form a fan of 360
individual receive beams from the array. This beamformed data is written
back in place into the 2-D matrix.

[0155](e) The 2-D matrix is then read in the frequency direction and the
64 k complex correlated samples are inverse Fourier transformed, using a
proprietary FFT algorithm, to convert the beam data back into the time
domain. This IFFT process is repeated for all 360 frequency domain beams
to generate the required fan of 360 beams in the time domain.

[0156](f) The complex time series beam data is then converted to magnitude
form and passed to the tracking and display processes.

[0157](g) The beam magnitude data can at this stage be displayed to the
operator to provide a raw detection display but in practice it is
necessary to add at least some echo association processing to ensure that
moving targets of spatial extent similar to the perceived threat are
displayed preferentially. These association processing and raw detection
display functions in the top end processing will now be discussed in more
detail

[0158]The magnitude beam data produced by the signal processing can be
used to provide a raw detection data display. In order to show the
perceived threat type clearly, additional data processing is required to
extract echoes that have metrics matching the threat class. Thus, the
processing chain used on the raw magnitude beam data streams is as
follows.

[0159](a) Associate echo clusters by collapsing the 64 k data samples,
which provide a resolution in the radial range direction of approximately
1.4 cm, to preferentially show targets with range extents approaching 1
metre, matching more closely those of a swimmer or diver.

[0160](b) Calculate the log-magnitude of the collapsed data.

[0161](c) Associate echo clusters from succeeding transmissions by feeding
them into a space-time store with a fading memory. The basic algorithm
employed here is to use a 2-D matrix store, which maps directly to the
surveillance cover. On each successive ping cycle, compare the processed
echo cluster with the data in the fading memory store. If the new echo
cluster signal is greater than that stored in the fading memory, use the
new signal to over-write the old data, if it is smaller, reduce the value
stored in the fading memory store by some fading factor. In this way,
target clusters that move are associated in the store and over time show
up as tracks in the fading memory store. The fading track mechanism
provides a degree of process gain due to the incoherent integration
process involved and the dynamic metrics of the track can provide clues
to the target classification.

[0162](d) Normalise this log-magnitude data to calculate the local
signal-to-noise ratio.

[0163](e) Map the orthogonal axes of the fading memory store to the radial
axes of the surveillance bracket and display.

[0164]Typical resultant detections from this fading memory store are shown
in FIGS. 18 and 19, which reproduce displays from a test installation,
using as target a diver equipped with a closed cycle rebreather SCUBA. In
FIG. 18, a diver has been detected, in a position indicated by the circle
100, at a range of 740.97 m and a bearing of 14.5°, with a fading
track showing the diver coming in from 830 m. The display of FIG. 19
shows that the diver has moved to a new position 102, at a range of
285.33 m and a bearing of 34.1°, showing the track of the diver
coming in from 400 m. It will be noted that the diver is detected
effectively despite a large amount of clutter caused by extraneous echoes
from fish and other subsea items. It should be noted that these are
results from an actual in-sea test and do not reflect the maximum range
and detection performance of the system.

[0165]There now follows a discussion of the tracking and classification
processing.

[0166]The raw magnitude data generated from the processes described
hereinbefore can be input to a proprietary tracking and classification
software package using Kalman filter techniques to cluster target-like
echoes and to track them with time. As above, track metrics are used to
classify likely target types using the dynamics of the detected target
movement to define possible threat types.

[0167]The results from this tracking and classification process are shown
overlaid on the fading memory detection data in FIG. 20. This shows the
track of the swimmer shown in FIGS. 18 and 19 in arriving at the position
102.

[0169](a) The FDFT approach is efficient only with element numbers such as
256 or 512, which match efficient FFT block lengths. The pseudo-circular
convolution algorithm is efficient for element numbers of say 360, and
thus matches better to the practical limits used in many operational
systems.

[0170](b) The curvature required for processing a cylindrical array as in
the present invention is much more than that used in the past with
conformal arrays. Whilst this could in principle be accommodated using
FDFT, it would impose constraints on the number of elements in the
cylindrical array, and the use of the rotationally symmetric wave
function as in the present invention is numerically more efficient with
other array sizes.

[0171](c) The pseudo-circular convolution algorithm of the present
invention is much more efficient in terms of number crunching
requirements than the FDFT approach.

[0172](d) Implementation by means of a fast convolution wave function
greatly simplifies the mathematics of the beamformer realisation and very
substantially reduces the amount of hardware--and hence the cost--needed
to implement the overall system. For instance in 1998 we referred to the
use of Butterfly Complex

[0173]Vector Processors, of which six might be required at say .English
Pound.20,000 each; but the present invention can perform the equivalent
function (using pseudo-circular convolution instead of FDFT) with a
single CPU which can be bought off the shelf for about .English
Pound.130.

[0174]Those skilled in the science will now appreciate that the invention
provides an underwater intruder detection system particularly appropriate
for spotting enemy combatants, insurgents and terrorists seeking to
attack civilian or military facilities by underwater assault.

[0175]The description set forth hereinbefore is intended to describe the
best method of performing the invention known to the applicants, but it
should be understood that various modifications and adaptations may be
possible.